Sklearn kurtosis

1. How do you calculate kurtosis in Python?
2. What does a kurtosis of 7 mean?
3. What does kurtosis tell us?

How do you calculate kurtosis in Python?

To calculate the sample skewness and sample kurtosis of this dataset, we can use the skew() and kurt() functions from the Scipy Stata librarywith the following syntax: skew(array of values, bias=False) kurt(array of values, bias=False)

What does a kurtosis of 7 mean?

A value of 6 or larger on the true kurtosis (or a value of 3 or more on the perverted definition of kurtosis that SPSS uses) indicates a large departure from normality. Very small values of kurtosis also indicate a deviation from normality, but it is a very benign deviation.

What does kurtosis tell us?

Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. A uniform distribution would be the extreme case.